This report contains a descriptive analysis of fisheries in Tela Bay, based on the sampled, time-series database of fish landings collected by CORAL and its partners.

Date Preparation

# ==== Data preparation ====

# Preparing columns
dat <- dat |> 
  # Using the cleaned common names as default
  mutate(nc_og = nombre_comun) |> 
  mutate(nombre_comun = str_to_title(nombre_comun_cln)) |> 
  # Adding "sp" to columns where the genus is present but no species is present
  mutate(species = if_else((is.na(species) & !is.na(genus)), 'sp', species)) |> 
  tidyr::unite(nombre_cientifico, genus, species, sep=' ', remove=F, na.rm=T) |> 
  # Factorizing relevant columns
  mutate(comunidad = as.factor(comunidad)) |> 
  mutate(zona_pesca = as.factor(zona_pesca)) |> 
  # Getting year, month, and year-month columns
  mutate(year = year(fecha), month=month(fecha), .after='fecha') |> 
  mutate(ym = paste(year, str_pad(month, 2, 'left', '0'), sep='-'), .after=month) |> 
  mutate(month = month.abb[month]) |> 
  # Factorizing year and month column
  mutate(year = as.factor(year)) |> 
  mutate(month = factor(month, levels=month.abb)) |> 
  # Converting weight to kg
  mutate(peso = peso/1000)

# Removing rows where no date is given
dat <- dat |> filter(!is.na(fecha))

# Removing outliers (detected based on IQR ranges specific to each
# genus/family) - based on length
dat <- dat |> 
  # A helper grouping variable that uses the family name if the scientific name
  # is not available
  mutate(taxa = if_else(is.na(nombre_cientifico), family, nombre_cientifico)) |> 
  group_by(taxa) |> 
  # Naming outliers for each taxa group
  mutate(isoutlier = anomalize::iqr(longitud)) |>
  ungroup()

# Separating those that are outliers for manual inspection - they don't look
# unreasonable, so not removing anything
outliers <- dat |> filter(isoutlier == "Yes")
# outliers |> select(all_of(idx)) |> View()

# Removing outlier related fields
dat <- dat |> 
  # filter(isoutlier == "No") |> 
  select(-isoutlier, -taxa)

General characteristics

1. Most-caught fish species

10 most-caught species by number and weight

Total captured weight for the 10-most caught species, split by year

2. Most-used gears

3. Catch-seasonality

Overall Catch-seasonality

Catch-seasonality split by fishing gear

4. Shannon-Diversity of caught species and gear by community

## [1] "Diversided de especias capturadas por comunidad:"
##        La Ensenada              Miami        Muelle Tela        Tela Centro 
##           1.679863           2.103792           2.092801           2.233354 
##            Tornabe Triunfo De La Cruz 
##           1.502238           2.438094
## [1] "Diversidad de especias capturadas por tipo de arte:"
##         Arpon    Chinchorro Linea De Mano          Nasa     Trasmallo 
##     1.6453484     2.1459931     2.1633648     0.6439435     1.9200773
## [1] "Diversidad de tipos de artes por comunidad:"
##        La Ensenada              Miami        Muelle Tela        Tela Centro 
##          0.1185480          0.3876737          0.0000000          0.9322189 
##            Tornabe Triunfo De La Cruz 
##          0.5211916          0.6580848

5. Biomass monitored per year (monitoring effort)

10-most caught species characteristics

1. Catch-seasonality (10-most caught species)

2. Proportion of catches that are mature

Proportion of mature catches by year

Proportion of mature catches by gear

Sexual maturity

Maturity data were only gathered for a small subset of the total sampling effort. The observations which contain maturity data have the following characteristics:

## [1] "Total number of observations with maturity data: 314"
## [1] "Date range: 2017-03-13" "Date range: 2017-10-31"
## [1] "Number of maturity observations by species:"
## 
## Euthynnus alletteratus      Lutjanus synagris      Ocyurus chrysurus 
##                      1                    284                      6 
##  Scomberomorus cavalla       Scomberomorus sp 
##                      3                     20

Considering that most observations are for Calale (Lutjanus synagris), the following two plots show the maturity and sex trends for only this species:

1. Seasonality of maturity status

2. Seasonality of sex